I calcualted a Gaussian Process model in Python using GPy:
ker0 = GPy.kern.Bias(input_dim=1,variance=1e-2)
...
m = GPy.models.GPRegression(x, y, ker0+ker2)
I can plot it with
m.plot()
plt.show
and it visualizes the points, the spline and the confidence limits. Now I want to extract the parameters and the confidence limits to use the data in another plot. My question is, how can I access these data.
if I print m I get
Name : GP regression
Objective : 31.9566881665
Number of Parameters : 4
Number of Optimization Parameters : 4
Updates : True
Parameters:
GP_regression. | value | constraints | priors
sum.bias.variance | 7.48802926977e-61 | +ve |
sum.spline.variance | -2.99999065833 | -3.0,-1.0 |
sum.spline.c | 19.8308670902 | 0.0,300.0 |
Gaussian_noise.variance | 50.2314402955 | +ve |
thx!
Try
m.sum.bias.variance
notice the m.
at the beginning.